Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Fait Poms

Fait Poms
Graduate Student, Stanford University

Website

Fait Poms is a CS PhD student at Stanford, where she is advised by Kayvon Fatahalian, as well as a research contractor for Oculus/Facebook. Fait’s PhD research focuses on designing algorithms and programmable systems for efficiently analyzing video. She has published and presented work at SIGGRAPH and CVPR on systems for large-scale video analysis and efficient 3D reconstruction using deep learning.

Sessions

11:50am–12:30pm Thursday, March 28, 2019
Scanner: Efficient video analysis at scale
Data Engineering & Architecture
 Location: 2008
Secondary topics:  Deep Learning, Media, Marketing, Advertising
Fait Poms (Stanford University), Will Crichton (Stanford University)
Average rating: ****.
(4.75, 4 ratings)
Video is now the largest source of data on the internet, so we need tools to make it easier to process and analyze. Alex Poms and Will Crichton offer an overview of Scanner, the first open source distributed system for building large-scale video processing applications, and explore real-world use cases. Read more.